With the development and popularization of the Internet, mobile Internet-based vehicle use is growing. In order to enhance the user's experience and improve competitiveness, it is usually necessary to acquire user information to determine the user's travel situation, infer the user's vehicle demand, and then push relevant information (such as travel coupons, etc.).
However, the existing information pushing method targeting the user's travel situation is usually based on the user's historical travel data to predict the user's vehicle demand probability, and then push the relevant information. This information pushing method cannot predict the user's vehicle demand and the relevant situation at the present time, resulting in insufficient timeliness and lack of pertinence of the information push.